AI
For decades, machine vision meant sending frames to a central server for processing. That architecture is breaking down as camera counts and resolutions climb.
Edge AI flips the model: inference runs on the camera or a nearby Jetson module, so only events and metadata travel the network. Latency drops below 30 ms, bandwidth collapses, and privacy improves because raw video never leaves the line.
At IPASS we design vision pipelines edge-first — custom YOLO models optimized with TensorRT, deployed to rugged hardware, and orchestrated with over-the-air updates so the fleet stays current.
The payoff is measurable: faster reject decisions, lower infrastructure cost, and inspection that scales to hundreds of cameras without a data-center bill.